The present invention relates to a method of and an apparatus for pattern inspection as one of the indispensable technologies for formation of patterns used in various industrial fields including fabrication of semiconductor devices. In particular, it relates to an apparatus for pattern inspection in which an image is formed with the use of such a device as a scanning electron microscope (SEM for visual inspection), laser scanning microscope, i-beam microscope, and scanning atomic force microscope and the pattern is inspected by observing the thus formed image.
One typical field of application of the present invention is the area of semiconductor manufacturing. In semiconductor manufacturing, the visual-inspection SEM (scanning electron microscope) is widely used for pattern inspection. Inspection of a pattern form with the use of a visual-inspection SEM is carried out, for example, through the following steps.
A sheet of wafer to be inspected, which has been taken out from a wafer cassette, is subjected to a pre-alignment process with an orientation flat portion or notch of the wafer used as a reference. Pre-alignment is a process to align the crystalline direction of the wafer in the moving direction of an XY-stage. After pre-alignment, the wafer is transported to and mounted on the XY-stage and placed in a specimen chamber which is kept in a vacuum. The wafer mounted on the XY-stage is then subjected to an alignment process with the use of an optical microscope mounted on the top of the specimen chamber. This alignment process is used to adjust the coordinate system of the pattern formed on the wafer to the coordinate system of the stage. To be more specific, the alignment is performed by comparing an image of the alignment pattern formed on the wafer magnified several hundred times by the optical microscope with a previously recorded reference image of the alignment pattern, and adjusting the positional coordinates of the stage so that the former image correctly registers with the latter, reference image. After the alignment, the wafer is shifted to a desired point to be inspected by movement of the stage. The point to be inspected is moved to the position irradiated by the scanning electron beam and thereby an SEM image is formed. The operator observes the formed SEM image based on the knowledge and information the operator has, and makes determinations as to the existence of pattern defects and defect classification.
The method mentioned above is defect classification in terms of the operator's vision. On the other hand if the object is converted to an optical microscopic image instead of a SEM image, an automatic classification is performed. This method of automatic classification is such that after extracting characteristics such as size and shape from the obtained defect image, a defect classifier performs an automatic classification based on the characteristics. For this purpose, a classifier such as neural network is in popular use. Such a method is disclosed in M. H. Bennett, "Automatic Defect Classification: Status and industry trends", pp. 210-220, Proceedings of SPIE, Vol. 2439, 1995, which is hereby incorporated by reference.
The main purpose of the defect classification is to accurately determine the existence of defects severe enough to cause failures in the devices (a so-called "killer defect") and to sort them out. By determining these killer defects, it becomes possible to effectively decrease defects affecting the product yield and thereby improve the product yield in a short period of time.
By Convention, defect classifications have generally been made by representing them by their geometric forms such as circles, squares, rectangles, and triangles or describing the sizes of the defects in absolute measures. Such ways of classification, however, have not always been suitable ways to segregate killer defects from non-killer defects.